# -*- coding:utf-8 -*-
import Image
import pytesseract
import os 

 
from PIL import Image,ImageDraw
#二值判断,如果确认是噪声,用改点的上面一个点的灰度进行替换  
#该函数也可以改成RGB判断的,具体看需求如何  
def getPixel(image,x,y,G,N):  
    L = image.getpixel((x,y))  
    if L > G:  
        L = True  
    else:  
        L = False  
    nearDots = 0  
    if L == (image.getpixel((x - 1,y - 1)) > G):  
        nearDots += 1  
    if L == (image.getpixel((x - 1,y)) > G):  
        nearDots += 1  
    if L == (image.getpixel((x - 1,y + 1)) > G):  
        nearDots += 1  
    if L == (image.getpixel((x,y - 1)) > G):  
        nearDots += 1  
    if L == (image.getpixel((x,y + 1)) > G):  
        nearDots += 1  
    if L == (image.getpixel((x + 1,y - 1)) > G):  
        nearDots += 1  
    if L == (image.getpixel((x + 1,y)) > G):  
        nearDots += 1  
    if L == (image.getpixel((x + 1,y + 1)) > G):  
        nearDots += 1  
  
    if nearDots < N:  
        return image.getpixel((x,y-1))  
    else:  
        return None  
  
# 降噪   
# 根据一个点A的RGB值，与周围的8个点的RBG值比较，设定一个值N（0 <N <8），当A的RGB值与周围8个点的RGB相等数小于N时，此点为噪点   
# G: Integer 图像二值化阀值   
# N: Integer 降噪率 0 <N <8   
# Z: Integer 降噪次数   
# 输出   
#  0：降噪成功   
#  1：降噪失败   
def clearNoise(image,G,N,Z):  
    draw = ImageDraw.Draw(image)  
  
    for i in xrange(0,Z):  
        for x in xrange(1,image.size[0] - 1):  
            for y in xrange(1,image.size[1] - 1):  
                color = getPixel(image,x,y,G,N)  
                if color != None:  
                    draw.point((x,y),color)


if __name__ == '__main__':
    path = os.path.abspath('./curriculum/capcha.png')

    image = Image.open(path)  
    #将图片转换成灰度图片  
    image = image.convert("L")  
    #去噪,G = 50,N = 4,Z = 4  
    clearNoise(image,70,4,4)  
    #保存图片  
    image.save(path)
    print pytesseract.image_to_string(image,'eng')




